Existing healthcare systems can collect healthcare data and incorporate the data into medical records. However, known systems assume a priori that data collected is in fact healthcare data and should be incorporated into such data records. Unfortunately, known healthcare systems lack the ability to assimilate raw data and make a determination if the raw data should be considered healthcare data. Rather, healthcare systems merely rely on a priori human knowledge to determine that the data will, in fact, be healthcare data.
Consider for example, U.S. patent application publication 2006/0293925 to Flom titled “System for Storing Medical Records Access Using Patient Biometrics”, filed Jun. 20, 2006. Flom contemplates updating medical records using patient biometrics. As biometric data is obtained, corresponding records are updated. Although useful when biometric data is known to be medically related, Flom fails to address conditions where generic or ambient data might or might not be medically related. In the Flom case, the biometric data is a priori determined to be related to medical records.
Another example includes U.S. patent application publication 2007/0365533 to Tran titled “Cuffless Blood Pressure Monitoring Application” filed May 12, 2006. Tran makes further progress by detecting data associated with individuals and detecting if they fall, their facial expressions, or other conditions. As with Flom, Tran assumes the data is a priori related to healthcare. Tran requires data-specific algorithms to determine if a condition is present. Tran also fails to offer insights into discriminating if generic or ambient data is medically relevant or not.
Unless the context dictates the contrary, all ranges set forth herein should be interpreted as being inclusive of their endpoints and open-ended ranges should be interpreted to include only commercially practical values. Similarly, all lists of values should be considered as inclusive of intermediate values unless the context indicates the contrary.
Thus, there is still a need for systems capable of recognizing that objects are in fact healthcare objects.